Picking route scheduling method, storage medium and electronic equipment
By selecting the highest priority order as the first order in the warehousing and logistics, and optimizing the picking route in combination with the shelf distance and driving line similarity, the problem of excessive picking routes caused by relying on shelf overlap in the existing technology is solved, and more efficient picking operations are achieved.
Patent Information
- Application Number
- CN202510138808.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-02-08
- Publication Date
- 2025-05-30
AI Technical Summary
The existing ones rely on the shelf overlapping degree to combine and combine singles, and still need to take a long picking route and cannot fully adapt to actual operation needs.
By selecting the order with the highest priority in order sorting as the first order, combining the distance between shelf points and the distance between shelf to adjacent inflection points, calculate the shortest route for each unit combination dispatch, and through the comparison of the similarity of the driving line, select the unit combination with the highest similarity of the driving line as the picking schedule.
It significantly reduces the total driving distance of the picking route, improves the overall efficiency of picking operations, and reduces transportation costs.
Smart Images
Figure CN120069719A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of warehousing and logistics, and in particular to a method for picking and scheduling routes, a storage medium and an electronic device. Background Art
[0002] In the field of warehousing and logistics, picking is one of the core links, and its efficiency directly affects the operating costs and customer satisfaction of the entire warehouse. Therefore, how to design a reasonable picking scheduling route to reduce the walking time for picking and improve the overall efficiency of picking has become an important issue that needs to be solved in the field of warehousing and logistics.
[0003] In traditional picking scheduling strategies, order merging is a common optimization method, which aims to reduce the walking path of pickers and improve picking efficiency by merging common goods in multiple orders. In this process, shelf overlap is an important indicator often used to evaluate the effect of order merging. Shelf overlap refers to the distribution of goods required by different orders on the same shelf or similar shelves. In theory, the higher the overlap, the shorter the walking path required to merge these orders for picking, and the higher the efficiency. However, it is found in practice that relying on shelf overlap for order merging does not always achieve the expected optimization effect. The reason is that the warehouse layout is complex and changeable, and the distribution of goods often follows specific inventory management strategies (such as first-in-first-out, classified storage, etc.). As a result, even if the shelf overlap is high, from a practical operational perspective, pickers still need to take a longer route in order to follow the optimal path or avoid repeated entry and exit of the same area. See Figure 1 As shown, the number of goods in order 1 is 2, the number of goods in order 2 is 3, and the number of goods in order 3 is 4. The order combinations include order 1 and order 2, order 1 and order 3, and order 2 and order 3; if the shelf overlap is calculated according to the existing order consolidation method, the shelf overlap of order 1 and order 3 is 2, which is greater than that of order 1 and order 2 (order 2 and order 3 are not considered because they are not the first order), so order 1 and order 3 are selected. However, it can be seen from the actual situation that order 1 and order 3 need to take a longer route.
[0004] In addition, factors such as the number of items in an order and the degree of urgency will also affect the optimization of picking routes, making the decision to merge orders based solely on shelf overlap appear overly simplistic and difficult to fully adapt to actual operational needs. Summary of the invention
[0005] In view of the above problems, the present application provides a method for picking and scheduling routes to solve the problem that the existing method of relying on the overlap of shelves for combining orders still requires a long route.
[0006] To achieve the above object, the inventor provides a method for picking and scheduling routes, which includes the following steps:
[0007] Select the order with the highest priority in the order sorting as the first order;
[0008] According to the number n of picking orders with attached orders, select the first m orders in the order sorting to obtain a combined order group, where m and n are positive integers, and m≥n, n≥2;
[0009] Calculate the shortest route for the scheduling of each combined order group according to the distance between shelf positions and the distance from the shelf to the adjacent inflection point;
[0010] Calculate the total route length for the scheduling of each combined order group according to the shortest route for the scheduling of each combined order group;
[0011] Calculate the total route length for the individual scheduling of the orders within each combined order group;
[0012] Calculate the similarity of the order picking routes according to the total route length for the scheduling of the combined order group and the total route length for the individual scheduling of the orders within the corresponding combined order group;
[0013] Select the combined order group with the highest similarity of the order picking routes as the picking scheduling for the first order combined order.
[0014] Further, the order with the highest priority in the order sorting is the urgent order, and the urgent order is an order that exceeds the agreed-upon duration.
[0015] Further, the sorting of the urgent orders is based on the duration by which the order exceeds the agreed-upon duration, and the order with a longer exceeded duration has a higher priority.
[0016] Further, the step of selecting the first m orders in the order sorting according to the number n of picking orders with attached orders to obtain a combined order group, where m and n are positive integers, and m≥n, n≥2, includes the following steps:
[0017] Obtain the number n of picking orders with attached orders, where n is a positive integer, n≥2;
[0018] Select the first m orders in the order sorting; where m is a positive integer, and m≥n;
[0019] According to the number n of picking orders with attached orders, take any n orders from the m orders and form a group, then order groups are formed;
[0020] Remove the order groups that do not include the first order in the order groups to obtain the combined order group.
[0021] Further, the step of calculating the shortest route for the scheduling of each combined order group according to the distance between shelf positions and the distance from the shelf to the adjacent inflection point includes applying the Floyd algorithm to calculate the shortest route for the scheduling of each combined order group;
[0022] This process continuously updates the D matrix through all possible intermediate points k until the shortest paths between all vertex pairs are found.
[0023] Further, in the step of calculating the moving line similarity based on the total length of the route for combined order scheduling and the total length of the routes for individual order scheduling within the corresponding combined order, the moving line similarity = (total length of the routes for individual order scheduling within the combined order - total length of the route for combined order scheduling) / total number of order items within the combined order.
[0024] Further, after the step of selecting the order with the highest priority in the order sorting as the first order, it further includes judging the number n of picking with order. If n = 1, then select the order that is not easily combinable among the first m orders in the order sorting as the first order.
[0025] Further, the orders that are not easily combinable include orders with volume and weight exceeding the preset thresholds.
[0026] A storage medium stores a computer program, and when the computer program is executed by a processor, it implements the method for picking and scheduling routes.
[0027] An electronic device includes a memory and a processor. A computer program is stored on the memory, and when the computer program is executed by the processor, it implements the method for picking and scheduling routes.
[0028] Different from the prior art, the above technical solution discovers which order combinations can produce the maximum route optimization effect by comparing the difference between the total length of the route for combined order scheduling and the total length of the routes for individual order scheduling within the corresponding combined order through the moving line similarity. It can intuitively reflect the degree of efficiency improvement of combined scheduling compared to individual scheduling. When the moving line similarity is relatively high, it indicates that combined scheduling significantly reduces the total driving distance, thereby improving the distribution efficiency and reducing the transportation cost.
[0029] The relevant descriptions in the above invention content are only an overview of the technical solution of this application. In order to enable those of ordinary skill in the art to more clearly understand the technical solution of this application, and then can be implemented according to the content recorded in the description and the drawings, and in order to make the above objects, other objects, features, and advantages of this application more easily understood, the following is described in conjunction with the specific implementation manners and drawings of this application. Description of the Drawings
[0030] The drawings are only used to show the principles, implementation manners, applications, features, and effects of the specific implementation manners of the present invention and other related contents, and should not be considered as a limitation to this application.
[0031] In the drawings of the description:
[0032] Figure 1 is the shelf layout diagram described in the background art;
[0033] Figure 2 is the method flowchart of the picking scheduling route described in the embodiment. Detailed implementation manners
[0034] To illustrate in detail the possible application scenarios, technical principles, implementable specific solutions, achievable objectives and effects of the present application, etc., the following will be described in detail with reference to the specific examples listed and in conjunction with the accompanying drawings. The embodiments described herein are only used to more clearly illustrate the technical solutions of the present application, so they are only examples and cannot be used to limit the protection scope of the present application.
[0035] Referring to "embodiment" herein means that the specific features, structures or characteristics described in connection with the embodiment may be included in at least one embodiment of the present application. The term "embodiment" appearing in various positions in the specification does not necessarily refer to the same embodiment, nor does it particularly limit its independence or relevance to other embodiments. In principle, in the present application, as long as there is no technical contradiction or conflict, the technical features mentioned in each embodiment can be combined in any way to form corresponding implementable technical solutions.
[0036] Unless otherwise defined, the meanings of the technical terms used herein are the same as those generally understood by those skilled in the technical field to which the present application belongs; the use of the relevant terms herein is only for describing specific embodiments and is not intended to limit the present application.
[0037] In the description of the present application, the term "and / or" is an expression used to describe the logical relationship between objects, indicating that three relationships may exist. For example, A and / or B means: there is A, there is B, and there is both A and B at the same time. In addition, the character " / " herein generally represents an "or" logical relationship between the associated objects before and after.
[0038] In the present application, terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual quantity, primary-secondary or order relationship, etc. between these entities or operations.
[0039] Without further limitations, in this application, the open-ended expressions such as "including", "comprising", "having" or other similar expressions used in a statement are intended to cover non-exclusive inclusion. These expressions do not exclude the existence of additional elements in a process, method or product including the said elements, so that a process, method or product including a series of elements may not only include those defined elements, but also include other elements not explicitly listed, or elements inherent to such a process, method or product.
[0040] Similar to the understanding in the "Examination Guidelines", in this application, expressions such as "greater than", "less than", "exceeding" are understood not to include the number itself; expressions such as "above", "below", "within" are understood to include the number itself. In addition, in the description of the embodiments of this application, the meaning of "multiple" is two or more (including two). Similar expressions related to "many", such as "multiple groups", "multiple times", etc., are understood in the same way, unless otherwise specifically defined.
[0041] In the description of the embodiments of this application, the spatially related expressions used, such as "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "perpendicular", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc., the indicated orientation or positional relationship is based on the orientation or positional relationship shown in the specific embodiment or the drawing. It is only for the convenience of describing the specific embodiments of this application or for the reader's understanding, rather than indicating or implying that the device or component referred to must have a specific position, a specific orientation, or be constructed or operated in a specific orientation. Therefore, it should not be construed as a limitation to the embodiments of this application.
[0042] See Figure 1 and Figure 2 As shown, a method for picking and dispatching routes discovers which order combinations can produce the greatest route optimization effect by comparing the total length of the routes of combined dispatching through the similarity of movement lines and the total length of the routes of individual dispatching of the orders within the corresponding combined dispatching. It can intuitively reflect the degree of efficiency improvement of combined dispatching compared to individual dispatching. When the similarity of movement lines is relatively high, it indicates that combined dispatching significantly reduces the total driving distance, thereby improving the distribution efficiency and reducing the transportation cost.
[0043] Combined with Figure 1 The method for picking and dispatching routes of this application is further described as including the following steps:
[0044] S1. Select the order with the highest priority in the order sorting as the first order;
[0045] S2. Select the top m orders in the order ranking according to the number n of picking orders with attached orders to obtain a combined order group, where m and n are positive integers, and m≥n, n≥2;
[0046] S3. Calculate the shortest route for dispatching each combined order group according to the distances between shelf positions and the distances from the shelf to the adjacent inflection points;
[0047] S4. Calculate the total route length for dispatching each combined order group according to the shortest route for dispatching each combined order group;
[0048] S5. Calculate the total route length for dispatching the orders in each combined order group separately;
[0049] S6. Calculate the moving line similarity according to the total route length for dispatching the combined order group and the total route length for dispatching the orders in the corresponding combined order group separately;
[0050] S7. Select the combined order group with the highest moving line similarity as the picking dispatching for the first combined order.
[0051] The priority ranking of the order ranking in the above step S1 is arranged in the order of urgent orders, orders that are not easy to combine, and orders that can be combined, that is, the priority of urgent orders in the above order ranking is the highest. The above urgent orders refer to the orders that have exceeded the agreed delivery or processing time with the customer. For the ranking of urgent orders, usually the time exceeding the agreement of the order is used as the main basis for ranking. Specifically, it is to rank according to the length of the actual time exceeding the agreement of each urgent order. The order with a longer exceeding time has a higher priority. By accurately calculating the exceeding time of each urgent order and ranking according to this, the resources can be most reasonably allocated, so that each link such as picking, packaging, and delivery is closely connected, and the urgent demand can be responded to at the fastest speed, minimizing the negative impact caused by delays. The above orders that are not easy to combine refer to the orders including those with volume and weight exceeding the preset threshold.
[0052] In the above step S2, according to the number n of picking orders with attached orders, select the top m orders in the order ranking to obtain a combined order group, where m and n are positive integers, and m≥n, n≥2. The number n of the above picking orders with attached orders refers to the number of orders carried by the picking personnel for one picking. The above top m orders in the order ranking include the first m orders starting from the first order at the beginning. Taking the top 5 orders in the order ranking as an example, then this will include the first order and the 4 orders following it. The above obtaining the combined order group can specifically include the following steps:
[0053] Obtain the number n of sorting orders with attached orders, where n is a positive integer, n≥2;
[0054] Select the top m orders in the order ranking; where m is a positive integer, and m≥n;
[0055] According to the number \(n\) of sorting belt orders, take \(n\) orders from \(m\) orders and form a group, then there will be order combinations formed;
[0056] Remove the order combinations that do not contain the first order in the order combinations, and obtain the combined order combinations.
[0057] The above-mentioned step S3 calculates the shortest route for scheduling each combined order combination according to the distance between shelf positions and the distance from the shelf to the adjacent inflection point, including the following steps:
[0058] First, it is necessary to draw a warehouse layout diagram, including the positions of each shelf, the position of the packing table, etc., that is, project the positions of each shelf and the packing table onto the route of the road map to form a warehouse layout diagram. The route in the above-mentioned road map is scaled down according to the actual road length of the store.
[0059] Then use the Euclidean distance formula to obtain the distance between shelf positions and the distance from the shelf to the adjacent inflection point from the warehouse layout diagram.
[0060] The distance between the above-mentioned shelf positions refers to the distance between the center points of one shelf and another shelf, that is, assuming the midpoint coordinates of one shelf are \((x 1 , y 1 ), and the midpoint coordinates of another shelf are \((x 2 , y 2 );
[0061] Then the distance between the shelf positions is
[0062] The distance from the above-mentioned shelf to the adjacent inflection point is the distance from the shelf center to the adjacent inflection point, and its calculation refers to the distance between the shelf positions.
[0063] After that, apply the Floyd algorithm to calculate the shortest route for scheduling each combined order combination, specifically including:
[0064] Organize the distance between the shelf positions and the distance from the shelf to the adjacent inflection point into a matrix A, where A[u, v] represents the direct distance from point u to point v;
[0065] Let D be the distance matrix. Initially, D[u, v] = A[u, v], that is, the distance matrix D starts as the direct distance matrix A.
[0066] Three-layer loop:
[0067] For k from 1 to n;
[0068] For i from 1 to n;
[0069] For j from 1 to n;
[0070] If the path from i to j can be made shorter by using vertex k as an intermediate point, then update D[i,j] to D[i,k] + D[k,j], where n is the number of vertices.
[0071] This process continuously updates the distance matrix D through all possible intermediate points k until the shortest paths between all vertex pairs are found, that is, the shortest routes for each combined order scheduling are obtained. When calculating the sum of the distances of the shortest routes for each combined order scheduling, the distances will be added according to the pre-set shelf moving line.
[0072] In the above step S6, according to the total length of the route of the combined order scheduling and the total length of the routes of the individual order schedulings within the corresponding combined order, when calculating the moving line similarity, the difference in the total length of the routes between the combined order scheduling and the individual scheduling can be compared through the moving line similarity. In some embodiments, the moving line similarity = (the total length of the routes of the individual order schedulings within the combined order - the total length of the route of the combined order scheduling) / the total number of order items within the combined order. The sum of the distances of the total length of the routes of the individual order schedulings within the combined order will also be added according to the pre-set shelf moving line.
[0073] See Figure 1 As shown, the starting point and the ending point are both at the packing table (in some embodiments, the starting point and the ending point may be different), the shelf width is 0.6 meters, the length is 2 meters, and the road width is 1.2 meters. The number of items in Order 1 is 2, the number of items in Order 2 is 3, and the number of items in Order 3 is 4. The order combinations include Order 1 and Order 2, Order 1 and Order 3, Order 2 and Order 3 (excluded). When calculating the moving line similarity, then:
[0074] The total length of the route of the combined scheduling of Order 1 and Order 2 is 2 * 3 + 1.2 * 3 + 2 * 3 = 15.6;
[0075] The total length of the routes of the individual order schedulings within the combined order of Order 1 and Order 2 = 2 * 3 + 1.2 * 3 + 2 * 3 + 2 * 3 + 1.2 * 3 + 2 * 3 = 31.2.
[0076] That is, the moving line similarity of Order 1 and Order 2 is (31.2 - 15.6) / 5 = 3.12
[0077] And so on, the moving line similarity of Order 1 and Order 3 is (43.6 - 28) / 6 = 2.6
[0078] 3.12 > 2.6. Therefore, adopt the combined order of Order 1 and Order 2.
[0079] Of course, in actual applications, there are also cases where orders cannot be combined into a single order, that is, the number of orders with picking tickets is 1. Therefore, before the step of selecting the order with the highest priority in the selected order sorting as the first order, the number n of orders with picking tickets can also be judged. If n = 1, then select the order that is not easily combined into a single order among the first m orders in the order sorting as the first order.
[0080] The present application also provides a storage medium storing a computer program, which when executed by a processor implements the method of the picking scheduling route.
[0081] The computer program involved in the embodiment can be stored in a storage medium, which includes but is not limited to magnetic disks, magnetic tapes, magnetic cards, floppy disks, flash memories, optical discs, optical cards, read-only memories (ROMs), random access memories (RAMs), erasable programmable ROMs (EPROMs), and electrically erasable programmable ROMs (EEPROMs), etc., and also includes other biological, physical or chemical structures that can achieve the same or equivalent functions as the above-listed storage media, such as units with information storage capabilities like DNA, RNA, proteins, etc. In a specific embodiment, the storage medium involved can be one of the above medium types or a combination of the above medium types. In different embodiments, the computer program involved in the embodiment can be centrally stored in a single medium or distributedly stored in multiple media. The memory containing the storage medium can be a non-volatile memory or a random access memory. These storage media can be built into the device or can be an external device or a part of an external device connected to the device involved in the embodiment. In some embodiments, the memory with the storage medium is deployed locally; in other embodiments, a scheme of deploying the memory away from the processor can also be adopted, such as a network-attached memory accessed via an RF circuit or an external port and a communication network, where the communication network can be the Internet, one or more internal networks, local area networks (LANs), wide area wireless networks (WLANs), storage area networks (SANs), etc., or a suitable combination thereof, as long as the computer device can access the memory. In addition, the computer program involved in the embodiment can be stored in plaintext / ciphertext form or can be designed as training data and implicitly stored in the parameter state of a deep neural network or other machine learning models through model training and integration and recombination.
[0082] The present application also provides an electronic device, which includes a memory and a processor, and a computer program is stored on the memory, which when executed by the processor implements the method of the picking scheduling route.
[0083] The processor described in the embodiments of the present application can be implemented by hardware, firmware, software, or a combination thereof. It can use circuits, one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), central processing units (CPUs), controllers, microcontrollers, microprocessors, or at least one of the like, and also includes other physical, biological, or chemical structures that can implement functions similar to or equivalent to those of the above-listed processors, such as biological neurons, quantum computing units, DNA computing units, etc., so that the processor can execute some steps, all steps, or any combination of the steps mentioned in the computer programs or methods involved in the various embodiments of the present application.
[0084] Finally, it should be noted that although the above embodiments have been described in the text and drawings of the specification of the present application, the patent protection scope of the present application cannot be limited thereby. Any technical solution obtained by replacing or modifying an equivalent structure or equivalent process based on the essential concept of the present application and using the content recorded in the text and drawings of the specification of the present application, as well as any technical solution directly or indirectly implementing the technical solutions of the above embodiments in other related technical fields, etc., are all included in the patent protection scope of the present application.
Claims
1. A method for picking and dispatching routes, characterized in that: The following steps are involved: Select the order with the highest priority in the order sorting as the first order; According to the number of orders n, select the first m orders in the order sorting to obtain the order combination, where m and n are positive integers, and m≥n, n≥2; Calculate the shortest route for each combined dispatch based on the distance between shelf locations and the distance from the shelf to the adjacent turning point; According to the shortest route of each combined dispatch, the total length of each combined dispatch is calculated; Calculate the total length of the routes for each order combination; Calculate the similarity of the movement routes based on the total length of the route for combined dispatch and the total length of the route for the orders in the corresponding combined dispatch. The order combination with the highest similarity in movement lines is selected as the picking schedule for the first order combination.
2. The method for picking and scheduling routes according to claim 1, characterized in that: Urgent orders have the highest priority in the order sorting, and the urgent orders are orders that exceed the agreed time.
3. The method for picking and scheduling routes according to claim 2, characterized in that: The emergency orders are sorted based on how long the order exceeds the agreed time. The longer the order exceeds the agreed time, the higher the priority.
4. The method for picking and dispatching routes according to claim 1, characterized in that: The step of selecting the first m orders in the order sorting according to the number n of picking orders to obtain a combined order combination, where m and n are positive integers and m≥n, n≥2, includes the following steps: Get the number of sorting orders n, where n is a positive integer, n ≥ 2; Select the first m orders in the order ranking; where m is a positive integer and m≥n; According to the number of sorting orders n, we randomly select n orders from m orders and group them into a group, then we will form Order combination; Removal The order combinations that do not include the first order are combined to obtain the combined order combination.
5. The method for picking and dispatching routes according to claim 1, characterized in that: The step of calculating the shortest route for each combined dispatch according to the distance between the shelf points and the distance from the shelf to the adjacent turning point includes applying the Floyd algorithm to calculate the shortest route for each combined dispatch; This process continues to update the D matrix through all possible intermediate points k until the shortest paths between all vertex pairs are found.
6. The method for picking and dispatching routes according to claim 1, characterized in that: In the step of calculating the movement line similarity based on the total length of the routes scheduled by the single combination and the total length of the routes scheduled individually for the orders in the corresponding single combination, the movement line similarity = (total length of the routes scheduled individually for the orders in the single combination - total length of the routes scheduled by the single combination) / total number of order items in the single combination.
7. The method for picking and scheduling routes according to claim 1, characterized in that: After the step of selecting the highest priority order in the order sorting as the first order, the step also includes determining the number n of picking orders. If n=1, the order that is not easy to merge among the first m orders in the order sorting is selected as the first order.
8. The method for picking and dispatching routes according to claim 7, characterized in that: The orders that are difficult to combine include orders whose volume and weight exceed a preset threshold.
9. A storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the method for picking and scheduling routes as described in any one of claims 1 to 8.
10. An electronic device, characterized in that It includes a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method for picking and scheduling routes as described in any one of claims 1 to 8 is implemented.